1. Field of the Invention
The present invention concerns a method for acquisition and generation of a time-resolved image series by means of magnetic resonance technology, as is particularly suitable in the context of medical examinations for representation of the movement cycle of an anatomical organ with a quasi-periodic movement.
2. Description of the Prior Art
Magnetic resonance imaging is a medical imaging modality that has been successfully established for years. Described with significant simplification, magnetic fields of different strengths and spatial and temporal characteristics hereby induce nuclear magnetic resonances in a subject to be examined that cause detectable signals to be emitted. The detected measurement data are typically arranged in a two-dimensional or three-dimensional mathematical space or domain (known as k-space) that is related with the image space or domain via a Fourier transformation.
In recent times the field of dynamic MRI has been developed, meaning the acquisition of a temporally resolved image series with which movement cycles can be represented. A typical application of dynamic MRI known as CINE imaging of organs that exhibit a quasi-periodic movement, such as, for example, the heart, the lungs, the abdomen or the blood flow through vessels.
Dynamic MRI requires a fast acquisition of the individual images of the temporal image series in order to freeze and temporally resolve the motion-caused changes in the subject to be imaged. Since MRI images often receive long image (data) acquisition times that are not acceptable for this purpose, various further developments are known in order to accelerate the process of the image acquisition. One successfully employed option is that a portion of the total data that are necessary to reconstruct the image are not acquired during the acquisition process and that the missing data are generated using a priori knowledge and/or assumptions that are made about the reconstruction process.
When a Cartesian sampling trajectory is used in the acquisition of the measurement data, meaning that the measurement data are acquired so as to be arranged along a Cartesian grid in k-space, various methods exist for acceleration of the acquisition of measurement data in dynamic MRI. It is common to these methods that the number of the actually-acquired k-space lines per image is decreased by certain k-space lines being skipped-over during the acquisition of the measurement data. Differences primarily exist in the manner of how specific assumptions, a priori knowledge and/or additionally acquired measurement signals are used in order to fill in the k-space lines that were skipped-over in the data acquisition with data reconstructed (interpolated) from the measurement data.
Examples of these methods are known under the names UNFOLD and TSENSE and are described in the following articles: Madore B. et al., “Unaliasing by Fourier-Encoding the Overlaps Using the Temporal Dimension (UNFOLD), Applied to Cardiac Imaging and fMRI”, Magn. Reson. Med. 42:813-828, 1999; Peter Kellman, Frederick H. Epstein, Elliot R. McVeigh. “Adaptive sensitivity encoding incorporating temporal filtering (TSENSE)”. Magn. Reson. Med. 45:846-852, 2001.
Both methods use sampling schemes in which only every Ath k-space line in both the spatial and in the temporal directions is acquired in the acquisition of the measurement data of the image series (A is a whole-number) while the other k-space lines are skipped-over (not acquired, i.e. no data are entered therein). When the temporal image series is calculated directly from the measurement data, this image series exhibits a multiple-A aliasing in the form of artifacts known as ghost images.
In the UNFOLD method, this image series is Fourier-transformed along the time axis. In frequency space the spectrum of the image series contains A sub-components, namely are component corresponding to the spectrum of the desired image series and A-1 components corresponding to the unwanted ghost images. While the ghost images overlap in the image series, the ghost images are separated in the frequency spectrum: the spectrum of the desired components is localized around the zero frequency while the spectra of the ghost images are shifted by the value Np/A (Np=number of the individual images of the image series). The UNFOLD method uses a low-pass filter in order to suppress the unwanted components. In general, however, the spectra of the unwanted components and the spectra of the ghost images overlap to a certain degree. This overlap cannot be separated by the filtering, such that in general the filtering leads either to a temporal smearing (due to filtering of high-frequency components) or to a retention of ghost image artifacts (due to insufficient suppression of the corresponding components) in the image series.
The TSENSE method is based on the UNFOLD method. The measurement data are acquired with multiple coil elements and, for the removal of the aliasing in the image series, the respective, different coil sensitivity profiles are additionally used that are determined directly from the under-sampled measurement data using the UNFOLD method. An improved elimination of the aliasing results in this manner.
Further methods based on the same sampling schemes are known under the names kt-BLAST, kt-SENSE and TGRAPPA and are described in the following articles: Jeffrey Tsao, Peter Boesiger, Klaas P. Pruessmann. “k-t BLAST and k-t SENSE: Dynamic MRI with high frame rate exploiting spatiotemporal correlations”, Magn. Reson. Med. 50:1031-1042, 2003; Felix A. Breuer, Peter Kellman, Mark A. Griswold, Peter M. Jakob. “Dynamic autocalibrated parallel imaging using temporal GRAPPA (TGRAPPA)”. Magn. Reson. Med. 53:981-985, 2005.
A disadvantage of these methods is that an intensification of artifacts and/or noise occurs, causing, a higher temporal blurring and a lower temporal resolution compared with a completely acquired static subject, or a completely acquired temporal image series with a decreased spatial resolution.
Furthermore, in MRI it is known that non-Cartesian methods of k-space sampling can be advantageous in the acquisition of the measurement data, in particular the use of radial-like sampling patterns of k-space. These methods are primarily characterized by their robustness with regard to an under-sampling and with regard to artifacts, in particular with regard to movement artifacts.
Attempts therefore exist to use non-Cartesian k-space sampling patterns in dynamic MRI in order to reduce remaining artifacts and/or to increase the signal-to-noise ratio and/or to attain further acceleration. For example, a number of methods that all exhibit severe disadvantages in comparison to a Cartesian sampling are discussed in the document by Hansen, Michael S. et al., “k-t BLAST reconstruction from non-Cartesian k-t space sampling”, Magn. Res. Med. 55:85-91, 2006. For example, the disclosed methods exhibit reconstruction times of multiple hours, which is why they can be used only very rarely in clinical imaging, since this leads to unwanted delays in clinical workflows and high costs.
Another method that is used both for static and dynamic MRI is known under the name PROPELLER MRI and is, for example, described in the documents by J. G. Pipe, “Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI; Application to Motion Correction”, ISMRM 1999, abstract Nr. 242 and “Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI; Application to Contrast-Enhanced MRA”, ISMRM 1999, abstract Nr. 157 and “Motion Correction with PROPELLER MRI: application to head motion and free-breathing cardiac imaging”, Magn. Reson. Med. 42:963-969, 1999.
For MRI using the PROPELLER technique k-space is covered in a blade-like manner with respective right-angled k-space segments (Engl.: often also designated as “blades” or “stripes”) that are rotated relative to one another around a central k-space point.
Among other things, it is advantageous in this type of k-space sampling that an unwanted movement of the subject to be examined that can occur between the acquisition of two k-space segments can be determined. Depending on the type of the movement, this can either be calculated out in the reconstruction of the image data or at least be accounted for such that artifacts as a consequence of the patient movement are suppressed comparably well.
In the article by J. G. Pipe entitled “Periodically Rotated Overlapping ParallEL Lines with Enhanced Reconstruction (PROPELLER) MRI; Application to Contrast-Enhanced MRA”, ISMRM 1999, abstract Nr. 157, the PROPELLER technique is used in a special embodiment for dynamic contrast agent examination. The method described therein, however, cannot be used without further measures for representation of quasi-periodic movement cycles, for example the movement of the heart.